A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Recommender Systems for the People - Enhancing Personalization in Web Augmentation
2015
ACM Conference on Recommender Systems
Preserved Fulltext
Therefore, we present a novel approach to empower user script developers to build more personalized augmenters by utilizing collaborative filtering functionality as an external service. ...
Thus, script writers can build recommender systems into arbitrary websites, in fact operating across multiple website domains, while guarding privacy and supplying provenance information. ...
Since we base on established item-item collaborative filtering algorithms, the evaluation of prediction accuracy was not a goal for this paper. ...
dblp:conf/recsys/WischenbartFRW15
fatcat:gthli4muvrac5h6yjgpnu623ja
Recommender Systems for Software Project Managers
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
2021
Evaluation and Assessment in Software Engineering
unpublished
doi:10.1145/3463274.3463951 fatcat:swnokxx5o5aklmschqgjt43u7u
doi:10.1145/3463274.3463951 fatcat:swnokxx5o5aklmschqgjt43u7u
The design of recommendation systems is based on complex information processing and big data interaction. ...
This personalized view has evolved into a hot area in the past decade, where applications might have been proved to help for solving problem in the software development field. ...
By using Lenskit and Mahout framework and API, this experiment explores the model of user-based collaborative filtering and item-based collaborative filtering algorithms [13]. ...
arXiv:2108.04311v1
fatcat:kwxlipm7cbbwdm7qdvgfdudjqu
Book Recommendation System using Matrix Factorization
2021
International Journal for Research in Applied Science and Engineering Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
By victimisation filtering strategies for pre-processing the information, recommendations area unit provided either through collaborative filtering or through content-based Filtering. ...
In recent years, recommender systems became more and more common and area unit applied to a various vary of applications, thanks to development of things and its numerous varieties accessible, that leaves ...
Recommender systems operate via machine learning algorithms. Typically, these algorithms may be classified into 2 classescontent-based and collaborative filtering. ...
doi:10.22214/ijraset.2021.36025
fatcat:prj7lnn6tzclzhrkzt4ualrgmi
Vote Goat
2018
The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The demonstration provides an interactive movie recommendation system using a speech-based natural language interface. ...
In this demonstration we introduce Vote Goat, a conversational recommendation agent built using Google's Di-alogFlow framework. ...
Instead of a single model or framework, Vote Goat supports multiple recommendation algorithms and libraries: Tensorflow-based neural collaborative filtering models served via Google CloudML [5] , PyTorch ...
doi:10.1145/3209978.3210168
dblp:conf/sigir/DaltonAM18
fatcat:hsijellginhozf6y4qxp3i3kzm
Communicating online information via streaming video: the role of user goal
2017
Online information review (Print)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
There are various ways and methods used in video recommendation which are purely statistical. These would give recommendations to users based on either their previous search or other criteria. ...
In this paper we propose a user specific category based promotion, we propose and provide for characterization of individual content as well as social attributes that help distinguish each user class. ...
an item (content-based approaches) or the user's social environment (collaborative filtering approaches). ...
doi:10.1108/oir-06-2016-0152
fatcat:zvbsvyeqszgkjfih4bf2nqwjqi
TRIPLE Delieverable 5.7: Additional Services Updated
2023
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2023; you can also visit the original URL.
The file type is application/pdf.
The work has been organised in the following 6 tasks: ● T5.1: Third-party applications integration ● T5.2: Recommender system ● T5.3: Trust building system ● T5.4: Visualisation ● T5.5: Open annotation ...
receive in their personal page dedicated documents suggestions, according to their previous history of interactions with GoTriple. ...
• "research-item-most-popular" recommends documents to a user using the most popular algorithm • "research-item-personalized" recommends documents to a user using a collaborative filtering algorithm • ...
doi:10.5281/zenodo.7701285
fatcat:3vc6yeie6baslncdlkuejl4keq
A building permit system for smart cities: A cloud-based framework
2018
Computers, Environment and Urban Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this paper we propose a novel, cloud-based framework to support citizens and city officials in the building permit process. ...
The proposed framework is completely cloud-based, such that any city can deploy it with lower initial as well as maintenance costs. ...
In order to generate permit recommendations, we employed item-based collaborative filtering. ...
doi:10.1016/j.compenvurbsys.2018.03.006
fatcat:suc3t5dwi5cdnjyhtsf7b67chi
Application Programming Interface for the Cloud-Based Management of Gamified eGuides
2020
Information
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
and gamification functionality provided on a cloud. ...
The popularity of smartphones and widespread access to mobile internet removed earlier barriers to reliance on mobile applications run on visitors' own devices for guidance in tourist attractions. ...
project and subcontractors who knowingly or not contributed to the requirement elicitation and testing processes of the eMused.eu API. ...
doi:10.3390/info11060307
fatcat:pgiz3he3c5bxddajbgpell2ama
D3.2- INITIAL REPOSITORY OF INTERLINKERS AND PARTNERSHIP TOOLS
2021
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2024; you can also visit the original URL.
The file type is application/pdf.
actually listed in the initial repository available online at https://demo.interlink-project.eu/catal. ...
Deliverable D3.2 is a deliverable of type OTHER and is constituted by the collection of knowledge and software resources that implement the INTERLINKERs made available in the first version of the INTERLINK ...
Figure 1 shows the graphical interface of the INTERLINKERs catalogue, as has been implemented in the first prototype of the INTERLINK Collaborative Environment (T4.4), where items can be filtered according ...
doi:10.5281/zenodo.10670124
fatcat:tmnncityqvevhdiraos2olscw4
E-Learning Recommendation System for Big Data Based on Cloud Computing
2021
International Journal of Emerging Technologies in Learning (iJET)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This system used big data tools such as Hadoop and Spark to enhance data collection, storage, analysis, processing, optimization, and visualization, furthermore based on cloud computing infrastructure ...
To fix this problem, this paper proposes a model of an E-learning recommendation system that will suggest and encourage the learner in choosing the courses according to their needs. ...
Content-based filtering Fig. 2. Collaborative filtering
Fig. 4 . 4 Fig. 4. ...
doi:10.3991/ijet.v16i21.25191
fatcat:6wpafrtjcfanjeuq5bchfdim3e
A Context-Aware Recommender System for Personalized Places in Mobile Applications
2016
International Journal of Advanced Computer Science and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Places are recommended based on what other users have visited in the similar context conditions. Recommender system puts rates for each place in each context for each user. ...
The aim of the work in this paper is to make a context-aware recommender system, which recommends places to users based on the current weather, the time of the day, and the user's mood. ...
Often the application of recommender systems uses Collaborative filtering and content of the list. ...
doi:10.14569/ijacsa.2016.070360
fatcat:wnpz6tzw5vc3tlueajklofhrhu
Using social data as context for making recommendations
2009
Proceedings of the 1st Workshop on Context, Information and Ontologies - CIAO '09
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Web-based knowledge systems support an impressive and growing amount of information. ...
This work bridges the gap between the user and system searches by analyzing the virtual existence of a user and making interesting recommendations accordingly. ...
The cold-start problem is recommending items of interest to new users who do not have any related preferences in their profile. ...
doi:10.1145/1552262.1552269
fatcat:oe4hdaaqprc4nlbocbwyeadjdy
Recommender systems for IoT enabled quantified-self applications
2019
Evolving Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
phones, genomic data, and cloud-based services. ...
Next-generation QS applications could include more recommender tools for assisting the users of QS systems based on their personal self-tracking data streams from wearable electronics, biosensors, mobile ...
Acknowledgements Open access funding provided by Graz University of Technology. ...
doi:10.1007/s12530-019-09302-8
fatcat:4gtq3rnnbnfgtf6njd7kwiyh7e
Machine learning based e-commerce application using progressive web apps for online shopping of seasonal fruits
2022
International Journal of Health Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Here, the details of all kinds of seasonal fruits are collected along with the geo location tags and stored in the cloud to provide easy access to everyone. ...
The application is developed using open cart framework, angular and uses the progressive web application development features. ...
Based on the collaborative filtering technique the application recommends products based on user's interest and browsing history. For example, users who buys apple will also buy a mangoes. ...
doi:10.53730/ijhs.v6ns3.5809
fatcat:434wadmvsfcnzim5svmwppplyu
Improving Recommendation Systems with User Personality Inferred from Product Reviews
[article]
2023
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2023; you can also visit the original URL.
The file type is application/pdf.
Other Versions
types contribute differently to recommendation performance: open and extroverted personalities are most helpful in music recommendation, while a conscientious personality is most helpful in beauty product ...
Personality is a psychological factor that reflects people's preferences, which in turn influences their decision-making. ...
Liangming Pan's efforts in his help in proofreading this work. ...
arXiv:2303.05039v2
fatcat:ztj2mpqocndm3hf5x2ccsbu6ce
« Previous
Showing results 1 — 15 out of 3,931 results